rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Nonlinear Dynamics in Computational Neuroscience
  name:
    name part: Corinto, Fernando.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Torcini, Alessandro.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 141 p. 50 illus., 34 illus. in color. online resource.
  abstract: This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the development of engineering devices and platforms for neuromorphic computation. Written by leading experts in such diverse fields as neuroscience, physics, psychology, neural engineering, cognitive science and applied mathematics, the book reflects the remarkable advances that have been made in the field of computational neuroscience, an emerging discipline devoted to the study of brain functions in terms of the information-processing properties of the structures forming the nervous system. The contents build on the workshop "Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT," which was held in Torino, Italy in September 2015.
  table of contents: Introduction -- Next generation neural mass models -- Unraveling brain modularity through its slow oscillations -- Characterization of Neural Signals in Preclinical Studies of Neural Plasticity using Nonlinear Time Series Analysis -- Functional Cliques in Developmentally Correlated Neural Networks -- Chimera states in pulse coupled neural networks: the influence of dilution and noise -- Nanotechnologies for Neurosciences -- Memristor and Memristor Circuit Modelling based on Methods of Nonlinear System Theory -- A memristor-based cell for complexity.
  note: edited by Fernando Corinto, Alessandro Torcini.
  subject:
    topic: Computational intelligence
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: Neurosciences
  subject:
    topic: Statistical physics
  subject:
    topic: Computational Intelligence
  subject:
    topic: Mathematical Models of Cognitive Processes and Neural Networks
  subject:
    topic: Neurosciences
  subject:
    topic: Applications of Nonlinear Dynamics and Chaos Theory
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: PoliTO Springer Series
  identifier: 9783319710488
  identifier: https://doi.org/10.1007/978-3-319-71048-8
  record info:
    record creation date: 180619
    record change date: 20191220131237.0
    record identifier: 978-3-319-71048-8